Semi-autonomous sensory-motor control for upper limb prostheses

在过去的几十年里，人们一直在努力建立假肢和人类神经系统之间的人机界面[1]。这些接口提供了一定程度的控制，在极少数情况下，可以向用户传递一些感觉。尽管如此，先进的双向感觉-运动控制界面的临床转化仍然有限。一个理想的假肢装置应该模仿生物学上的感觉和驱动能力。考虑到人类四肢复杂的结构和神经控制，这是一个极端的挑战。虽然近年来机电一体化技术发展迅速，使我们能够接近这一理想，但最先进的人机界面所提供的假肢和用户之间的信息传输仍然非常低。即使推进接口技术，神经接口也不太可能复制自然感觉运动控制的所有方面。虽然假肢不能完全通过神经“重新连接”到使用者身上，以利用他们的决策和感觉/控制能力，但有可能通过自己的智能来增强设备。这种方法是一个完全不同的概念的assistivesktualization相对于当前的国家的最先进的，促进机器人控制器从一个简单的解码器的用户意图到智能代理与用户合作，完成功能任务。在这种方法中，用户只发送关于高级目标的信息（例如，抓住杯子）而运动的细节（例如，特定的接近轨迹、抓握类型和大小）主要是下意识地展开，从而模仿健康受试者如何控制他们的肢体。因此，感觉-运动控制将成为半自主的，就像大多数自然任务一样，这些任务是在没有有意识地控制所有身体自由度和整合感觉反馈的情况下执行的。假肢控制的半自主方法已经初步探索，主要与感觉-运动回路的运动部分有关（例如，而半自主的完整感觉-运动回路在假肢系统中还没有被探索过。在这个项目中，我们提出了一个半自主控制系统的开发，集成电机命令与感官信息在闭环系统中的假肢，无论是在用户层面（有意识的感觉运动控制），并在AI代理水平（自主感觉运动控制）。这两个感觉-运动回路共同完成假肢的最终激活任务。

In the past decades, efforts have been made to establish man-machine interfacesbetween prostheses and the human nervous system [1]. These interfaces have providedsome level of control and, in rare cases, the possibility to transmit some sensation to theusers. Nonetheless, clinical translation of advanced bidirectional sensory-motor controlinterfaces has been limited. An ideal prosthetic device should mimic the sensing and actuation capabilities of thebiological counterpart. Considering the sophisticated structure and neural control ofhuman limbs, this is an extreme challenge. While the mechatronic technology has beendeveloping rapidly in recent years, allowing us to come close to this ideal, the informationtransfer between the prosthesis and the user offered by state-of-the-art man-machineinterfaces is still extremely low. Even advancing the interfacing technology, it is veryunlikely that neural interfaces can replicate all aspects of natural sensory-motor control. While the prosthesis cannot be fully neurally "re-connected" to the user to exploit theirdecision-making and sensory/control abilities, it is possible to enhance the device with itsown intelligence. This approach is a radically different conceptualization of an assistivesystem with respect to current state-of-the-art, promoting the robotic controller from asimple decoder of the user intent into an intelligent agent collaborating with the user inaccomplishing functional tasks. Within this approach, the user transmits information onlyabout a high-level goal (e.g., grasping a cup) while the details of the movements (e.g.,specific approach trajectory, grasp type and size) unfold mostly subconsciously, mimicking thereby how healthy subjects control their limbs. The sensory-motor control wouldtherefore become semi-autonomous, as for most natural tasks that are executed withoutconsciously controlling all the body degrees of freedom and integrating sensory feedback.The semi-autonomous approach to prosthesis control has been preliminary exploredmainly in relation to the motor part of the sensory-motor loop (e.g., from our researchgroup see the recent paper [2]) while semi-autonomous full sensory-motor loops havenever been explored in prosthetic systems. In this project we propose the development of a semi-autonomous control system forprostheses that integrate motor commands with sensory information in closed-loopsystems both at the user level (conscious sensory-motor control) and at an AI agent level(autonomous sensory-motor control). These two sensory-motor loops share the task ofthe ultimate activation of the prosthesis.